Downloaded 42 times
Uploaded byMark West
IoT Tech Day Smart Camera slides. Utrecht, April 2017.
The document outlines the process of building a smart security camera using Raspberry Pi Zero, Node.js, and AWS cloud services, focusing on creating a low-cost, portable, motion-activated device. It discusses the project's motivation, functional requirements, and details the integration of AWS Rekognition for image analysis to enhance alarm accuracy. The evaluation reveals both the advantages and limitations of using cloud services for real-time monitoring and analysis.
More Related Content
Similar to IoT Tech Day Smart Camera slides. Utrecht, April 2017.
IoT Tech Day Smart Camera slides. Utrecht, April 2017.
- 1. Building a SmartSecurity Camera with Raspberry Pi Zero, Node.js and The Cloud Mark West #iottechday
- 2. Who Am I? • IT Consultant at Bouvet. • Hacker and Maker. •Java, JavaScript, AI, Cloud & IoT. • Active member of javaBin - the Norwegian JUG. @markawest
- 3.
- 4.
- 5.
- 6. Project Requirements Functional • Monitor activity in the garden. • Send warning when activity detected. •Live video stream. Non-functional • In place as soon as possible. • Low cost. • Portable. @markawest
- 7.
- 8.
- 9. Pi Zero W Essentials Kit: €30 Camera Module: €28 Camera Adapter: €6 ZeroView: €9 Total Cost: €73 Hardware Shopping List @markawest
- 10.
- 11.
- 12. Motion (https://motion-project.github.io) • Open source motion detection software. • Excellent performance on the Raspberry Pi Zero. •Built-in Web Server for streaming video. • Detected activity or ‘motion’ triggers events. • Works out of the box. No need for additional programming. @markawest
- 13.
- 14.
- 15. How the Motion Software works 1 2 34 @markawest 1 2 3
- 16. How the Motion Software works 1 2 34 1 2 3 @markawest 1 2 3
- 17. How the Motion Software works 1 2 34 1 2 3 @markawest 1 2 3
- 18.
- 19. Project Requirements : Evaluation Functional • Monitor activity in the garden. • Send warning when activity detected. •Live video stream. Non-functional • In place as soon as possible. • Low cost. • Portable. @markawest
- 20.
- 21.
- 22.
- 23.
- 24. Project Requirements Reloaded Functional • Monitor activity in our garden. • Send warning when activity detected. •Live video stream. Non-functional • In place as soon as possible. • Low cost. • Portable. @markawest
- 25. Project Requirements Reloaded Functional • Monitor activity in our garden. • Send warning when human activity detected. •Live video stream. Non-functional • In place as soon as possible. • Low cost. • Portable. @markawest
- 26. Finding an Image Analysis Solution OpenCV • Use Face Detection to find out if a human was in the snapshot. • Problem: What if the subject was facing away from the camera, or wearing a mask? TensorFlow •Train and use a Neural Network to find humans in the snapshot. • Problem: Potentially a fun project, but would take more time than I had available. @markawest
- 27.
- 28. AWS Rekognition • Part of Amazon Web Services suite of Cloud based services. • Image Analysis as a Service, offering a range of API’s. •Built upon Deep Neural Networks. • Officially launched in November 2016. • Alternatives: Google Vision, MicroSoft Computer Vision, Clarafai. @markawest
- 29.
- 30.
- 31.
- 32. AWS Software Developer Kit (SDK) • SDK’s exist for a range of programming languages and platforms. (including Python, Ruby, .NET, iOS, Go, C++ and Java) • Provides an API for consuming AWS Services. •For this project I used the Node.js AWS SDK. (including the upload from Camera to S3) @markawest
- 33.
- 34. AWS Lambda Functions • Code units, based on Java, C#, Python or Node.js • Serverless. •High availability out of the box. • Pay as you go model, with a generous free tier. • Native AWS SDK gives easy access to other AWS services. @markawest
- 35.
- 36.
- 37. AWS Step Functions • Coordinate and orchestrate Lambda Functions into Workflows or State Machines. • Launched in December 2016. •Defined via JSON files, displayed as visual workflows. • Provide the same benefits as AWS Lambda (High Availability, Serverless, Scalable, “Pay as you go” pricing model). @markawest
- 38.
- 39.
- 40.
- 41. Project Requirements : Evaluation Functional • Monitor activity in the garden. • Send warning when human activity detected. •Live video stream. Non-functional • In place as soon as possible. • Low cost. • Portable. @markawest
- 42. AWS Rekognition : ThePositives • Consistent results. •Successfully handles ’partial’ images. • Handles poor quality images (motion blur, poor lighting). • No more false alarms. @markawest
- 43. AWS Rekognition : Some Negatives • Black box. •Unable to provide feedback. • Struggles with ‘noisy’ pictures. • Results are only as good as the pictures you upload (resulting in a 80-95% hit rate). @markawest
- 44.
- 45.
- 46. Activity Timeline Improving AWS Rekognition Hit Rate @markawest Activity Event Start 1 Activity Event Stop 23 4 5 Most Central Activity
- 47.
- 48. Improving AWS Rekognition Hit Rate Upload One Snapshot when activity detected •Lower cost, due to less calls to the AWS stack. • Potentially lower hit rate. Upload Many Snapshots when activity detected • Higher cost due to increased calls to the AWS stack. • Potentially higher hit rate. @markawest
- 49. Some Benefits of Using AWS • Very easy to get started with, due to Free Tier, automated infrastructure and good documentation. •Large ecosystem with a broad range of services. • Serverless - so hot right now! @markawest
- 50. Some Drawbacks of Using AWS • Developer Tooling for Lambda Functions not yet mature. • Step Functions need a graphical editor. •Potential for vendor lock-in. @markawest
- 51.
- 52. S3 for Web Hosting • Created a HTML Report listing all False Alarm snapshots. •Report updated by a Lambda Function triggered by a timer. • Hosted on S3 as a static website. @markawest
- 53.
- 54. please rate mytalk in the official IoT Tech Day app @markawest